Particulate Research Articles

Persistent Environmental Injustice due to Brake and Tire Wear Emissions and Heavy-Duty Trucks in Future California Zero-Emission Fleets.

The adoption of zero-emission vehicles (ZEVs) offers multiple benefits for the climate, air quality, and public health by reducing tailpipe emissions. However, the environmental justice implications of the nonexhaust emissions from future ZEV fleets for near-roadway communities remain unclear. Here, we model the on-road fine particulate matter (PM2.5) emissions across all California counties and assess the near-roadway exposure disparities at the census block group level in the Los Angeles County in 2050, when almost all passenger vehicles are projected to be ZEVs. We found that promoting zero-emission heavy-duty trucks generates more air quality benefits for disadvantaged communities than light-duty passenger vehicles. Persistent disparities in near-roadway PM2.5 levels, however, exist due to the remaining brake and tire wear emissions and increased truck traffic in disadvantaged communities. We recommend implementing fleet-specific ZEV policies to address brake and tire wear emissions and optimizing freight structures to address these persistent environmental justice issues in California.

Application of Biomass-Based Triboelectrification for Particulate Matter Removal

Electrostatic fields are crucial for achieving the highly efficient filtration of airborne pollutants. However, the dissipation of static charges over time, especially under humid conditions, limits their practical application. In this study, we present a self-charging air filter (SAF) powered by a triboelectric nanogenerator (TENG). This SAF is integrated into a commercial mask, termed SAFM, which can effectively capture and degrade airborne pollutants without requiring an external power source. By leveraging the triboelectric effect during breathing, the TENG within the SAFM continuously replenishes static charges, maintaining the triboelectric field. The system employs a cellulose aerogel/Ti3C2Tx composite as the electron donor and an esterified cellulose-based electrospun nanofiber as the electron acceptor. Remarkably, the triboelectric field significantly enhances filtration performance, with the SAF achieving up to 95.7% filtration efficiency for particulate matter as small as 0.3 μm. This work underscores the potential of TENG-powered triboelectric fields in the development of multifunctional, human-machine interactive facemasks.

Association between long-term exposure to fine particulate air pollution and risk of death attributed to esophageal cancer in Taiwan

ABSTRACT The International Agency for Research on Cancer (IARC) classifies exposure to fine particulate matter (PM2.5) air pollution as carcinogenic to humans (Group I), most frequently associated with lung cancer. Airborne air pollutants may be associated with other sites of cancer, although few studies have examined this avenue of research. Esophageal cancer mortality rates vary substantially across townships in Taiwan, a fact that suggests environment influence. Therefore, the aim of this study was to investigate the association between long-term exposure to ambient PM2.5 and deaths attributed to esophageal cancer in 66 municipal areas across Taiwan. To conduct this study, annual PM2.5 levels were determined taking into account age-standardized esophageal cancer mortality rates in male and female residents of these municipalities from 2012 to 2021. The annual PM2.5 levels of each municipality were divided into tertiles and computed adjusted risk ratio (RR) using weighted-multiple regression analyses controlling for municipal lung cancer deaths, urbanization level, and physician density. Men residing in those areas with intermediate PM2.5 tertile levels (18.96–25.19 ug/m3) were found to have an adjusted RR of 1.22 (1.15–1.30) and those of residing areas with the highest tertiles levels (25.20–29.48 ug/m3) exhibited an RR of 1.11 (1.051.18). However, in women in the same municipalities, a significant inverse association was found between PM2.5 levels and mortality attributed to esophageal cancer, 0.82 (95% CI = 0.65-1.04) and 0.61 (95% CI = 0.47-0.79), respectively. These findings suggest that long-term exposure to PM2.5 increases the risk of developing esophageal cancer in men in Taiwan.

An ILC2-chitinase circuit restores lung homeostasis after epithelial injury.

Environmental exposures increase the risk for severe lung disease, but specific drivers of persistent epithelial injury and immune dysfunction remain unclear. Here, we identify a feedback circuit triggered by chitin, a common component of airborne particles, that affects lung health after epithelial injury. In mice, epithelial damage disrupts lung chitinase activity, leading to environmental chitin accumulation, impaired epithelial renewal, and group 2 innate lymphoid cell (ILC2) activation. ILC2s, in turn, restore homeostasis by inducing acidic mammalian chitinase (AMCase) in regenerating epithelial cells and promoting chitin degradation, epithelial differentiation, and inflammatory resolution. Mice lacking AMCase or ILC2s fail to clear chitin and exhibit increased mortality and impaired epithelial regeneration after injury. These effects are ameliorated by chitinase replacement therapy, demonstrating that chitin degradation is crucial for recovery after various forms of lung perturbation. Thus, the ILC2-chitinase response circuit may serve as a target for alleviating persistent postinjury lung epithelial and immune dysfunction.

Particulate Matter-Induced Emerging Health Effects Associated with Oxidative Stress and Inflammation.

Environmental pollution continues to increase with industrial development and has become a threat to human health. Atmospheric particulate matter (PM) was designated as a Group 1 carcinogen by the International Agency for Research on Cancer in 2013 and is an emerging global environmental risk factor that is a major cause of death related to cardiovascular and respiratory diseases. PM is a complex composed of highly reactive organic matter, chemicals, and metal components, which mainly cause excessive production of reactive oxygen species (ROS) that can lead to DNA and cell damage, endoplasmic reticulum stress, inflammatory responses, atherosclerosis, and airway remodeling, contributing to an increased susceptibility to and the exacerbation of various diseases and infections. PM has various effects on human health depending on the particle size, physical and chemical characteristics, source, and exposure period. PM smaller than 5 μm can penetrate and accumulate in the alveoli and circulatory system, causing harmful effects on the respiratory system, cardiovascular system, skin, and brain. In this review, we describe the relationship and mechanism of ROS-mediated cell damage, oxidative stress, and inflammatory responses caused by PM and the health effects on major organs, as well as comprehensively discuss the harmfulness of PM.

Independent and interactive effects of particulate matter and meteorological factors on hand, foot and mouth disease in Fuyang.

Previous research has demonstrated the influence of environmental factor on the occurrence of infectious diseases. However, there is insufficient and conflicting evidence regarding the association between Hand, foot and mouth disease (HFMD) and environmental variables, particularly the interaction of environmental variables. This study aims to investigate the individual and interactive effects of particulate matter (PM) and meteorological factors on HFMD incidence in Fuyang. The generalized additive models were combined with distributed lag non-linear models to assess the individual effects between PM and meteorological factor on HFMD incidence in Fuyang. Subsequently, a product term was incorporated into the model to investigate the interaction between PM and meteorological factors. Temperature and PM2.5 were identified as the two primary risk factors for HFMD, with relative risks (RR) of 1.586(1.493,1.685) and 1.349(1.325,1.373), respectively. Furthermore, PM exhibited a synergistic effect with meteorological factors. For instance, the RR values for PM2.5 in relation to HFMD were 1.029 (95% CI: 1.024-1.035) and 1 0.117 (95% CI: 1 0.108 - 11 0.127) under different temperature group categories. Notably, HFMD predominantly affects children under the age of five years old and infants aged between zero to one year old demonstrate heightened susceptibility to environmental variables. The results showed that both PM and meteorological factors were risk factors for HFMD, with evidence of an interaction between these variables. These findings have important implications for local HFMD incidence prediction and the development of effective prevention strategies.

Planetary health and mental health

Climate change is the greatest global health threat of the twenty-firstcentury. Greenhouse gas emissions and the resulting rise in average temperatures are directly linked to heatwaves, droughts, water and food shortages, extreme weather events, rising sea levels and migration movements as well as the loss of biodiversity and the alteration and degradation of ecosystems as we know them. Current estimates suggest that societies need to show much greater efforts to ensure that the global average temperature does not rise by more than 1.5 °C by 2029. Not only climate change but also other man-made factors, such as noise, light, particulate matter and plastics are threatening the health of the planet and therefore inevitably human health as well, both physical and mental health. Poorer planetary health also has an impact on human mental health. This article extends the DGPPN 2023 position paper on climate change and mental health to include the concept of planetary health. In particular, the normative dimension of the Canmore Declaration on Planetary Health, the concept of transdisciplinarity and specific calls for action are presented with their relevance to psychiatry, psychotherapy and mental health and the associations are graphically illustrated.

Influence of Oil and Gas End-Use on Summertime Particulate Matter and Ozone Pollution in the Eastern US.

The influence of oil and gas end-use activities on ambient air quality is complex and understudied, particularly in regions where intensive end-use activities and large biogenic emissions of isoprene coincide. In these regions, vehicular emissions of nitrogen oxides (NOx≡NO + NO2) modulate the oxidative fate of isoprene, a biogenic precursor of the harmful air pollutants ozone, formaldehyde, and particulate matter (PM2.5). Here, we investigate the direct and indirect influence of the end-use emissions on ambient air quality. To do so, we use the GEOS-Chem model with focus on the eastern United States (US) in summer. Regional mean end-use NOx of 1.4 ppb suppresses isoprene secondary organic aerosol (OA) formation by just 0.02 μg m-3 and enhances abundance of the carcinogen formaldehyde by 0.3 ppb. Formation of other reactive oxygenated volatile organic compounds is also enhanced, contributing to end-use maximum daily mean 8-h ozone (MDA8 O3) of 8 ppb. End-use PM2.5 is mostly (67%) anthropogenic OA, followed by 20% secondary inorganic sulfate, nitrate and ammonium and 11% black carbon. These adverse effects on eastern US summertime air quality suggest potential for severe air quality degradation in regions like the tropics with year-round biogenic emissions, growing oil and gas end-use and limited environmental regulation.

Assessment of Physical and Mechanical Parameters of Spun-Bond Nonwoven Fabric.

The selection of an appropriate fabric for technical applications, such as protective masks, hinges on a thorough understanding of the fabric's physical and mechanical properties. This study addresses the challenge of selecting the optimal material structure for the upper layer of a protective mask, aiming to ensure adequate breathability while providing effective filtration against airborne particles and contaminants. We assessed and compared the physical-mechanical properties of five polymer spun-bond nonwoven fabrics from different suppliers. Our comprehensive evaluation included, as follows: a visual inspection; light permeability analysis; mass and thickness measurements; elongation and tensile strength tests; breathing resistance assessments; and filter penetration tests with paraffin oil. The results revealed significant variations in performance among the samples, with one fabric consistently outperforming the others across multiple parameters. Notably, this top-performing fabric met or exceeded the EN 149:2001+A1:2009 standard for breathing resistance and filtration efficiency and, in combination with additional filter layers, met the requirements or exceeded class FFP2 (filtering face piece). This study underscores the importance of meticulous material selection and quality control in optimizing PPE (personal protective equipment) performance and user safety, providing valuable insights for mask manufacturers and healthcare professionals.

Robust Ridge-MM Estimator in Restricted Additive Partially Regression Model

This paper, utilized the Restricted Partially Additive Regression Model to analyze air quality data in Baghdad governorate, with a focus on addressing multicollinearity issues among independent variables and outliers in the dependent variable. Through the implementation of classical estimators, ridge estimators, robust estimators, and the imposition of non-random constraints on the parametric parts of the model Through method of Robust Ridge-MM Estimator in Restricted Additive Partially Regression Model, the study aimed to assess the model's effectiveness in dealing with air pollution challenges during the summer season. Results obtained through the use of pre-built packages and algorithms in the R programming language indicated that integrating non-random constraints with robust estimators positively impacted the accuracy of estimating functions. Furthermore, certain variables, such as PM10 (airborne particles with an aerodynamic diameter of up to 10 micrometres), were found to have a significant impact on air quality This is through the parameter values. Non-linear effects were observed for some non-parametric variables. The study highlights the importance of understanding the effects of air pollutants on public health and emphasizes the urgent need for quick solutions to mitigate these negative effects. Paper type: Research paper.

Outdoor Air Pollution Relates to Amygdala Subregion Volume and Apportionment in Early Adolescents.

Outdoor air pollution is associated with an increased risk for psychopathology. Although the neural mechanisms remain unclear, air pollutants may impact mental health by altering limbic brain regions, such as the amygdala. Here, we examine the association between ambient air pollution exposure and amygdala subregion volumes in 9-10-year-olds. Cross-sectional Adolescent Brain Cognitive Development SM (ABCD) Study ® data from 4,473 participants (55.4% male) were leveraged. Air pollution was estimated for each participant's primary residential address. Using the probabilistic CIT168 atlas, we quantified total amygdala and 9 distinct subregion volumes from T1- and T2-weighted images. First, we examined how criteria pollutants (i.e., fine particulate matter [PM 2.5 ], nitrogen dioxide, ground-level ozone) and 15 PM 2.5 components related with total amygdala volumes using linear mixed-effect (LME) regression. Next, partial least squares correlation (PLSC) analyses were implemented to identify relationships between co-exposure to criteria pollutants as well as PM 2.5 components and amygdala subregion volumes. We also conducted complementary analyses to assess subregion apportionment using amygdala relative volume fractions (RVFs). No significant associations were detected between pollutants and total amygdala volumes. Using PLSC, one latent dimension (LD) (52% variance explained) captured a positive association between calcium and several basolateral subregions. LDs were also identified for amygdala RVFs (ranging from 30% to 82% variance explained), with PM 2.5 and component co-exposure associated with increases in lateral, but decreases in medial and central, RVFs. Fine particulate and its components are linked with distinct amygdala differences, potentially playing a role in risk for adolescent mental health problems.

Assessment of the microbial contamination in “Do It Yourself” (DIY) stores - a holistic approach to protect workers’ and consumers’ health

IntroductionIn “Do-It-Yourself” (DIY) stores, workers from the wood department are considered woodworkers. Given the health risks associated with woodworking, particularly from fungi and their metabolites, this study aims to assess microbial contamination and health risks for both workers and customers.MethodsThe study was developed in 13 DIY stores in Lisbon Metropolitan Area, Portugal. It employed a comprehensive sampling approach combining active (MAS-100, Andersen six-stage, Coriolis μ, and SKC Button Aerosol Sampler) and passive (electrostatic dust collectors, surface swabs, e-cloths, settled dust, filters from vacuumed dust, filtering respiratory protection devices, and mechanical protection gloves) methods to assess microbial contamination. A Lighthouse Handheld Particle Counter HH3016- IAQ was used to monitor the particulate matter size, temperature, and humidity.ResultsThe wood exhibition area presented the highest fungal load, while the payment area exhibited the highest bacterial load. MAS-100 detected the highest fungal load, and surface swabs had the highest bacterial load. Penicillium sp. was the most frequently observed fungal species, followed by Aspergillus sp. Mycotoxins, namely mycophenolic acid, griseofulvin, and aflatoxin G1, were detected in settled dust samples and one filter from the vacuum cleaner from the wood exhibition area. Cytotoxicity evaluation indicates the wood-cutting area has the highest cytotoxic potential. Correlation analysis highlights relationships between fungal contamination and particle size and biodiversity differences among sampling methods.DiscussionThe comprehensive approach applied, integrating numerous sampling methods and laboratory assays, facilitated a thorough holistic analysis of this specific environment, enabling Occupational and Public Health Services to prioritize interventions for accurate exposure assessment and detailed risk management.

Impact of Nanoparticle Addition and Ozone Pre-Treatment on Mesophilic Methanogenesis in Temperature-Phased Anaerobic Digestion

Biodegradable organic waste offers significant opportunities for resource recovery within the frame of the circular economy. In this work, the effects of carbon-encapsulated iron nanoparticles and ozone pre-treatments in the mesophilic methanogenic stage of a temperature-phased an-aerobic digestion have been studied using biochemical methanogenic potential (BMP) tests and modeling simulation. To do that, digestates from a pre-treated thermophilic acidogenic reactor that co-digested sludge and wine vinasse were used. The addition of nanoparticles favored the removal of particulate matter, which increased by 9% and 6% in terms of total solids and volatile solids, respectively. When combined with ozone pre-treatment, these increases were 27% and 24%, respectively, demonstrating enhanced AD efficiency. The dose of iron nanoparticles encapsulated in carbon did not result in a statistically significant increase in methane production when sludge and vinasse were used as feedstock. The combination of nanoparticles with the ozone pre-treatment significantly improved the methanogenic phase of the second stage, increasing the methane production yield by 22% and reducing the lag phase from 10 days to 3 days, according to the modified Gompertz model.

A comparative analysis of an aerosol dry deposition microscale model for overhead powerlines insulators

Aerosol particles deposition on overhead power line insulators may significantly threaten electric systems, affecting dielectric properties and potentially causing surface discharges and service interruptions, leading to economic consequences. This study addresses this challenge by evaluating a dedicated microscale deposition model that integrated into an advanced air quality (AQ) modeling system. The microscale model integration into the AQ system aims to improve predictions of equivalent salt deposit density (ESDD), a key measure of insulator contamination. This enhancement is crucial for improving system resilience and reliability. The microscale model’s performance in reconstructing particulate matter (PM) deposition fluxes onto XP-70 porcelain-disk electrical insulator is assessed against measured ESDD data collected across various regions in Italy during several experimental campaigns. In order to better understand the specific phenomena impacting PM deposition, the microscale model is compared to the state-of-the-art Zhang deposition model used in CAMx. The analysis reveals that the microscale model tends to overestimate measured ESDD values and predicts higher deposition velocities than the Zhang model. These results suggest potential modelling differences between the two models, including variations in obstacle parameterizations, influence of particle aerodynamics, and dispersion modelling in the near-wall region.

Cleistocalyx nervosum var. paniala mitigates oxidative stress and inflammation induced by PM10 soluble extract in trophoblast cells via miR-146a-5p

Air pollution poses a significant global concern, notably impacting pregnancy outcomes through mechanisms such as DNA damage, oxidative stress, inflammation, and altered miRNA expression, all of which can adversely affect trophoblast functions. Cleistocalyx nervosum var. paniala, known for its abundance of anthocyanins with diverse biological activities including anti-mutagenic, antioxidant, and anti-inflammatory properties, is the focus of this study examining its effect on Particulate Matter 10 (PM10) soluble extract-induced trophoblast cell dysfunction via miRNA expression. The study involved the extraction of C. nervosum fruit using 70% ethanol, followed by fractionation with hexane, dichloromethane, and ethyl acetate. Subsequent testing for total phenolics, flavonoids, anthocyanins, and antioxidant activity revealed the ethyl acetate fraction (CN-EtOAcF) as possessing the highest phenolic and anthocyanin content along with potent antioxidant activity, prompting its selection for further investigation. In vitro studies on HTR-8/SVneo cells demonstrated that 5–10 µg/mL PM10 soluble extract exposure inhibited cell proliferation, migration, invasion, and induced apoptosis. However, pretreatment with 20–80 µg/mL CN-EtOAcF followed by 5 µg/mL PM10 soluble extract exposure exhibited protective effects against PM10 soluble extract-induced damage, including inflammation inhibition and intracellular ROS suppression. Notably, CN-EtOAcF down-regulated PM10-induced miR-146a-5p expression, with SOX5 identified as a potential target. Overall, CN-EtOAcF demonstrated the potential to protect against PM10-induced harm in trophoblast cells, suggesting its possible application in future therapeutic approaches.

Estimation methods for the variance of Birnbaum-Saunders distribution containing zero values with application to wind speed data in Thailand.

Thailand is currently grappling with a severe problem of air pollution, especially from small particulate matter (PM), which poses considerable threats to public health. The speed of the wind is pivotal in spreading these harmful particles across the atmosphere. Given the inherently unpredictable wind speed behavior, our focus lies in establishing the confidence interval (CI) for the variance of wind speed data. To achieve this, we will employ the delta-Birnbaum-Saunders (delta-BirSau) distribution. This statistical model allows for analyzing wind speed data and offers valuable insights into its variability and potential implications for air quality. The intervals are derived from ten different methods: generalized confidence interval (GCI), bootstrap confidence interval (BCI), generalized fiducial confidence interval (GFCI), and normal approximation (NA). Specifically, we apply GCI, BCI, and GFCI while considering the estimation of the proportion of zeros using the variance stabilized transformation (VST), Wilson, and Hannig methods. To evaluate the performance of these methods, we conduct a simulation study using Monte Carlo simulations in the R statistical software. The study assesses the coverage probabilities and average widths of the proposed confidence intervals. The simulation results reveal that GFCI based on the Wilson method is optimal for small sample sizes, GFCI based on the Hannig method excels for medium sample sizes, and GFCI based on the VST method stands out for large sample sizes. To further validate the practical application of these methods, we employ daily wind speed data from an industrial area in Prachin Buri and Rayong provinces, Thailand.

Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth

Abstract. Ambient fine particulate matter (PM2.5) is the leading global environmental determinant of mortality. However, large gaps exist in ground-based PM2.5 monitoring. Satellite remote sensing of aerosol optical depth (AOD) offers information to help fill these gaps worldwide when augmented with a modeled PM2.5–AOD relationship. This study aims to understand the spatial pattern and driving factors of this relationship by examining η (PM2.5AOD) using both observations and modeling. A global observational estimate of η for the year 2019 is inferred from 6870 ground-based PM2.5 measurement sites and satellite-retrieved AOD. The global chemical transport model GEOS-Chem, in its high-performance configuration (GCHP), is used to interpret the observed spatial pattern of annual mean η. Measurements and the GCHP simulation consistently identify a global population-weighted mean η value of 96–98 µg m−3, with regional values ranging from 59.8 µg m−3 in North America to more than 190 µg m−3 in Africa. The highest η value is found in arid regions, where aerosols are less hygroscopic due to mineral dust, followed by regions strongly influenced by surface aerosol sources. Relatively low η values are found over regions distant from strong aerosol sources. The spatial correlation of observed η values with meteorological fields, aerosol vertical profiles, and aerosol chemical composition reveals that spatial variation in η is strongly influenced by aerosol composition and aerosol vertical profiles. Sensitivity tests with globally uniform parameters quantify the effects of aerosol composition and aerosol vertical profiles on spatial variability in η, exhibiting a population-weighted mean difference in aerosol composition of 12.3 µg m−3, which reflects the determinant effects of composition on aerosol hygroscopicity and aerosol optical properties, and a population-weighted mean difference in the aerosol vertical profile of 8.4 µg m−3, which reflects spatial variation in the column–surface relationship.

How to evaluate the reduction effect of the park on PM2.5? Exploratory application of the maximum and cumulative perspective

Urban parks have been widely proved to be effective in reducing particulate matter pollution, but there is still a knowledge gap in quantitatively evaluating their reduction effects. The purpose of this study is to develop a new method to quantify the reduction effect of PM2.5 in urban parks through high-precision spatio-temporal monitoring experiments in 22 typical urban parks in Shenyang, China, so as to fill this gap. In this study, the cubic polynomial function model was used for the first time to establish the relationship curve between PM2.5 concentration inside and outside the park at different distances. The results showed that the park PM2.5 reduction magnitude and distance were about 5.04–10.14 ug/m3 and 149.47–150.19 m, respectively. Partial correlation analysis revealed that the relationship between the reduction evaluation indexes and the environmental factors had time heterogeneity. The park's internal characteristics and surrounding building environment was the key factor affecting the park PM2.5 reduction effect. In addition, parks smaller than 4.71 hm2 demonstrated better PM2.5 reduction efficiency. In conclusion, this study provides a new quantitative approach to evaluating the park PM2.5 reduction effect and offers data-driven insights for optimizing park planning to enhance the permeability of these effects beyond park boundaries.

Evaluation of Current and Future Aviation Fuels at High-Pressure Rich-Quench-Lean-Type Combustor Conditions

Abstract Decarbonizing the aviation sector is one of the biggest challenges to minimize climate change effects associated with carbon dioxide emission. Sustainable aviation fuels will play a major role in this context especially for long-distance flights where hydrogen or all-electric propulsion systems do not present a feasible alternative. In addition, aromatic-free sustainable aviation fuels offer a promising solution to lower soot emissions of aeroengines. Jet A-1 as reference fuel, two blends, and two neat synthesized paraffinic kerosenes (SPKs) from hydroprocessed esters and fatty acids (HEFA) were tested to characterize the combustion behavior of drop-in/near drop-in fuels. Experiments in an optically accessible high-pressure rich-quench-lean (RQL)-type combustor at typical aeroengine conditions were performed using optical diagnostics, exhaust gas, and particle sampling measurements to delineate the fuel effects on spray, flame, and emission characteristics. Measurements were performed at pressures up to 10 bar, air preheating temperatures up to 773 K and primary zone equivalence ratios up to 1.66. Liquid fuel distribution and fuel placement were found to be sensitive to fuel properties. By contrast, no pronounced influence on flame position and shape were observed. As a consequence, NOx and CO emissions of the tested fuels differed only moderately. However, particulate matter measurements at the fuel richest operating condition showed a clear fuel ranking with the lowest particle emissions evident for the two neat HEFA-SPK samples. Moreover, the particle volume concentration at the fuel richest condition followed the expected trend with fuel H-content.

The role of leukocytes in cognitive impairment due to long-term exposure to fine particulate matter: A large population-based mediation analysis.

Our understanding of how fine particulate matter (PM2.5) impacts cognitive functioning is limited. Systemic inflammation processes may play a role in mediating this effect. This prospective cohort study used data from 66,254 participants aged 18+ between 2006 and 2015 from the Dutch Lifelines Cohort Study and Biobank. Causal mediation analysis was conducted to examine the impact of ambient PM2.5 exposure on cognitive processing time (CPT), using the change in white blood cell (WBC) count and its subtypes as potential mediators. Heightened PM2.5 exposure was associated with slower CPT (total effect=81.76×10-3, 95% confidence interval [CI] 59.51×10-3-105.31×10-3). The effect was partially mediated via increased WBC count (indirect effect [IE]=0.42×10-3, 95% CI 0.07×10-3-0.90×10-3), particularly driven by an increase in monocytes (IE=0.73×10-3, 95% CI 0.24×10-3-1.31×10-3). Systemic inflammation processes may partially explain the harmful effects of PM2.5 on cognitive functioning, why lower levels of systemic inflammation may help contain its neurotoxic effects. The pathways leading to the neurotoxic effects of fine particulate matter (PM2.5) are poorly understood. We analyzed data from over 66,000 participants using causal pathway analysis. Increased white blood cell (WBC) count mediates the effect of PM2.5 on cognitive functioning. Monocyte count played a crucial role in this low-pollution setting. Systemic inflammation may contribute to the neurotoxic effects of PM2.5.